Transfusion medicine history illustrated: Lawrence <scp>Bruce‐Robertson</scp>'s “syringe and cannula method” set used for blood transfusion in the management of casualties in the First World War, 1914–1918
Bibliographic record
Abstract
At the outbreak of WW1, Lawrence Bruce-Robertson (LBR) was a junior staff surgeon at the Hospital for Sick Children in Toronto1 having spent two years in postgraduate training in New York and Boston. At Bellevue Hospital in New York, he became involved in the newly emerging field of blood transfusion and was particularly influenced by Edward Lindeman2 who developed one of the early devices for indirect transfusion to replace the direct vessel-to-vessel surgical methods. Lindeman's technique using multiple syringes (before the days of citrate anticoagulation), although demanding, was less difficult than direct vessel-to-vessel transfusion and also allowed measurement of the volume transfused. While LBR was aware of the contemporary technical alternatives to Lindeman's, including the introduction of citrate anticoagulation, this was one which he commonly applied in his early practice. The transfusion set illustrated here, which belonged to LBR and is believed to have been used at No. 2 Canadian Casualty Clearing Station, is in the Museum in the Canadian Forces Health Services Training Center at Canadian Forces Base Borden. It conforms closely to his published description of the equipment3; his report includes a detailed account of the technique by which he was able to transfuse up to 1000 ccs at a single procedure. Commandant, Canadian Forces Health Services Training Centre, CFB Borden, ON, Canada, for allowing access to the artifact.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.110 | 0.055 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".